Units performing multiply and accumulate operations, herein known as "multiply-accumulate units", are known in the art. They are particularly useful as subunits of vector-matrix multipliers which, in turn, are elements of neural networks.
An overview of Very Large Scale Integration (VLSI) implementations of neural networks, each implementing a large number of vector-matrix multipliers, is given in the article by Mark A. Holler, "VLSI Implementations of Learning and Memory Systems: A Review", Proceedings of Ad. VanC in Neural Information Processing Systems, Vol. 3, Morgan Kaufman Publishers, 1991.
A parallel optoelectronic neural network processor is described in U.S. Pat. No. 5,008,833 to Agranat et al. A matrix W is entered into an array of photosensitive devices which may be charge coupled or charge injection devices. The elements of the matrix W are multiplied by the appropriate vector elements and the results are summed thereby to produce a state vector indicating the state of the neural network.